Chapter 12 Marketing Research Flashcards

Which of the following is true of relationships between variables?

A linear relationship is much simpler to work with than a curvilinear relationship.

If a consistent and systematic relationship is not present between two variables, then

there is no relationship

A _________blank relationship is one between two variables whereby the strength and/or direction of their relationship changes over the range of both variables.

curvilinear

In a certain town, when the number of automobiles owned went up, the number of automobile repair and service centers also went up consistently. This illustrates the concept of _________blank.

covariation

Yair is analyzing the relationship between the sales levels and profits. The data gathered by Yair on these two components gives a correlation coefficient of 0.88. This indicates that the relationship between the two components is most likely to be _________blank.

very strong

The Spearman rank-order correlation coefficient differs from the Pearson correlation coefficient in that the Spearman rank-order correlation

is used when variables have been measured using ordinal scales, whereas the Pearson correlation coefficient is used when variables have been measured using ratio scales.

Which of the following statements is true of correlation analysis?

The null hypothesis for the Pearson correlation coefficient states that the correlation coefficient is zero.

The coefficient of determination

ranges from .00 to 1.0.

If the coefficient of correlation between two variables is -0.6, the coefficient of determination will be

0.36.

Which of the following is true of a beta coefficient?

It shows the change in the dependent variable for each unit change in the independent variable.

The pattern of covariation around the regression line that is not constant around the regression line and varies in some way when the values change from small to medium and large is known as _________blank.

heteroskedasticity

The statistical procedure that results in equation parameters (a and b) that produce predictions with the lowest sum of squared differences between actual and predicted is called

ordinary least squares.

_________blank is an indicator of the importance of an independent variable in predicting a dependent variable.

Regression coefficient

Which of the following statements is true of model F statistics?

A larger F statistic indicates that the regression model has more explained variance than error variance.

In the context of the least squares procedure, any data point that does not fall on the regression line is the result of

unexplained variance.

In a regression model, if independent variables exhibit multicollinearity, then

the estimation of separate regression coefficients for the correlated variables becomes difficult.

_________blank is a statistical technique that uses information about the relationship between an independent or predictor variable and a dependent variable to make predictions.

Bivariate regression analysis

If a researcher is interested in measuring the effect of many independent variables on a dependent variable, they should use

multiple regression analysis.

Which of the following is an advantage of the partial least squares method of structural equation modeling?

Solutions can be obtained with both small and large samples.

_________blank is a statistical method that is an extension of multiple regression and helps researchers determine whether there are meaningful relationships between the variables shown in the structural model.

Partial least squares